PV MODULE LIFETIME FORECAST AND EVALUATION

Causes of degradation and performance improvementin a complete PV system for O&M activities

M. sC. Guillermo Oviedo Hernández (ESR 14)guillermo.hernandez@baywa-re.com

Horizon 2020

Marie Sklodowska Curie Actions

Innovative Training Networks

SOLAR-TRAIN Beginners WeekFreiburg, Germany, July 3rd – July 7th 2017

Shaded PV modules. Left: visual photo, right: thermal image. Source: PI Berlin

The research activities will be focused on PVperformance enhancement by improved O&M,through the analysis of monitoring data in order toidentify the most relevant effects causingdegradation and reduction in plant performance.

• Cloud-based data management • Data analysis for automated failure detection and diagnosis• Energy production forecast (irradiance and weather prognosis) • Solar economics (impact of degradation and O&M strategies)• Cybersecurity of PV SCADA systems• On-site technical inspections for PV module quality assessment:

I-V curve tracing Electroluminescence (EL) imaging Infrared (IR) thermography

Formerly known as Kenergia Sviluppo, istoday the leading independent PV plantsmanagement company operating in Italy,with a portfolio of over 400 MW of PV andwind plants put under control, many withfull Operation and Maintenance services.

• Which key performance indicators (KPIs) must be analysed and how, inorder to study the causes of performance degradation of PV plants?

• Which are the most suitable processes for analysing data sets recorded bymonitoring/SCADA systems?

• How to integrate effectively diagnostic methods into BayWa´s cloud-basedO&M platform for reducing operational costs and production losses?

Aerial IR inspection. Photo: Guillermo Oviedo

Theoretical framework

Theoretical study of thedifferent causes ofperformance degradation andpossible solutions during thelifetime of PV systems, as wellas monitoring data analysis.

months 11-13

PV data analysis

Development of suitable dataanalysis processes for theidentification of the relevantparameters out of PV plantmonitoring data sets. A marketresearch of suitable softwarefor analysing big data will becarried out, to see how it canbe integrated into BayWa´sO&M platform.

months 14-19

Case studies

Elaboration of case studies onPV plant performance, to beachieved mainly remotelythrough big data analysis,having access to a hugedatabase of hundreds of PVplants monitored andmaintained by BayWa r.e.Operation Services S.r.l. Fieldtrips to selected PV plants willbe scheduled.

months 20-31

Diagnostic methods

Setup of remote and on-siteeffective diagnostic methodsfor reducing operational costsand production losses based onthe results of the case studies.

months 32-43

New trends and technologies

Market and technical analysisabout new technologies andtheir effectiveness forperformance improvement ofPV systems.

months 44-46

PV plant in Germany. Photo: Guillermo Oviedo

Project summary Research topics to be covered

Research design

Research questions About BayWa r.e. Operation Services